373 research outputs found
Extracting textual overlays from social media videos using neural networks
Textual overlays are often used in social media videos as people who watch
them without the sound would otherwise miss essential information conveyed in
the audio stream. This is why extraction of those overlays can serve as an
important meta-data source, e.g. for content classification or retrieval tasks.
In this work, we present a robust method for extracting textual overlays from
videos that builds up on multiple neural network architectures. The proposed
solution relies on several processing steps: keyframe extraction, text
detection and text recognition. The main component of our system, i.e. the text
recognition module, is inspired by a convolutional recurrent neural network
architecture and we improve its performance using synthetically generated
dataset of over 600,000 images with text prepared by authors specifically for
this task. We also develop a filtering method that reduces the amount of
overlapping text phrases using Levenshtein distance and further boosts system's
performance. The final accuracy of our solution reaches over 80A% and is au
pair with state-of-the-art methods.Comment: International Conference on Computer Vision and Graphics (ICCVG) 201
Text Localization in Video Using Multiscale Weber's Local Descriptor
In this paper, we propose a novel approach for detecting the text present in
videos and scene images based on the Multiscale Weber's Local Descriptor
(MWLD). Given an input video, the shots are identified and the key frames are
extracted based on their spatio-temporal relationship. From each key frame, we
detect the local region information using WLD with different radius and
neighborhood relationship of pixel values and hence obtained intensity enhanced
key frames at multiple scales. These multiscale WLD key frames are merged
together and then the horizontal gradients are computed using morphological
operations. The obtained results are then binarized and the false positives are
eliminated based on geometrical properties. Finally, we employ connected
component analysis and morphological dilation operation to determine the text
regions that aids in text localization. The experimental results obtained on
publicly available standard Hua, Horizontal-1 and Horizontal-2 video dataset
illustrate that the proposed method can accurately detect and localize texts of
various sizes, fonts and colors in videos.Comment: IEEE SPICES, 201
Penyelenggaraan struktur penahan cerun rock shed: langkah mitigasi runtuhan tanah di Simpang Pulai - Blue Valley, Perak
Industri pembinaan merupakan industri yang sangat mencabar bukan sahaja di Malaysia malah di seluruh dunia yang merangkumi skop 3D dirty, difficult and dangerous. Industri ini juga meruapakan antara penyumbang terbesar KDNK iaitu sebanyak 7.4 peratus pada tahun 2016, walaupun industri ini antara penyumbang terbesar dari aspek keselamatan iaitu kemalangan (CIDB, 2017). Justeru itu, pihak yang bertanggungjawab seharusnya memandang serius mengenai masalah-masalah yang dihadapi supaya industri ini mampu bersaing di peringkat antarabangsa
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